numpy.delete() in Python
The numpy.delete() function returns a new array with the deletion of sub-arrays along with the mentioned axis.
Syntax:
numpy.delete(array, object, axis = None)
Parameters :
array : [array_like]Input array.
object : [int, array of ints]Sub-array to delete
axis : Axis along which we want to delete sub-arrays. By default, it object is applied to
flattened arrayReturn :
An array with sub-array being deleted as per the mentioned object along a given axis.
Code 1 : Deletion from 1D array
Python
# Python Program illustrating# numpy.delete()import numpy as geek#Working on 1Darr = geek.arange(5)print("arr : \n", arr)print("Shape : ", arr.shape)# deletion from 1D arrayobject = 2a = geek.delete(arr, object)print("\ndeleteing {} from array : \n {}".format(object,a))print("Shape : ", a.shape)object = [1, 2]b = geek.delete(arr, object)print("\ndeleteing {} from array : \n {}".format(object,a))print("Shape : ", a.shape) |
Output :
arr : [0 1 2 3 4] Shape : (5,) deleting arr 2 times : [0 1 3 4] Shape : (4,) deleting arr 3 times : [0 3 4] Shape : (4,)
Code 2 :
Python
# Python Program illustrating# numpy.delete()import numpy as geek#Working on 1Darr = geek.arange(12).reshape(3, 4)print("arr : \n", arr)print("Shape : ", arr.shape)# deletion from 2D arraya = geek.delete(arr, 1, 0)''' [[ 0 1 2 3] [ 4 5 6 7] -> deleted [ 8 9 10 11]]'''print("\ndeleteing arr 2 times : \n", a)print("Shape : ", a.shape)# deletion from 2D arraya = geek.delete(arr, 1, 1)''' [[ 0 1* 2 3] [ 4 5* 6 7] [ 8 9* 10 11]] ^ Deletion'''print("\ndeleteing arr 2 times : \n", a)print("Shape : ", a.shape) |
Output :
arr : [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11]] Shape : (3, 4) deleting arr 2 times : [[ 0 1 2 3] [ 8 9 10 11]] Shape : (2, 4) deleting arr 2 times : [[ 0 2 3] [ 4 6 7] [ 8 10 11]] Shape : (3, 3) deleting arr 3 times : [ 0 3 4 5 6 7 8 9 10 11] Shape : (3, 3)
Code 3: Deletion performed using Boolean Mask
Python
# Python Program illustrating# numpy.delete()import numpy as geekarr = geek.arange(5)print("Original array : ", arr)mask = geek.ones(len(arr), dtype=bool)# Equivalent to np.delete(arr, [0,2,4], axis=0)mask[[0,2]] = Falseprint("\nMask set as : ", mask)result = arr[mask,...]print("\nDeletion Using a Boolean Mask : ", result) |
Output :
Original array : [0 1 2 3 4] Mask set as : [False True False True True] Deletion Using a Boolean Mask : [1 3 4]
References :
https://docs.scipy.org/doc/numpy/reference/generated/numpy.delete.html
Note :
These codes won’t run on online IDE’s. Please run them on your systems to explore the working
.
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